A survey on visual data representation for smart grids control and monitoring

Abstract

Abstract The legacy grid is evolving towards an intelligent-rooted grid system, whose architectural components should be able to improve and adapt their performance according to learning experiences. In the long term, decision making and actions execution may become completely machine-autonomous tasks in smart grids due to the progress of artificial intelligence and machine learning techniques. However, in the short and medium terms, control and monitoring activities will still require human–computer interaction. Due to the inherent characteristics of the smart grids, all gathered and processed data are heterogeneous by nature, being necessary to create novel ICT-based tools and platforms able to offer a broader multi-dimensional control perspective for the energy industry. In this context, visualization plays a key role in facilitating the challenging tasks of monitoring, analyzing, and responding to the events in the smart grid. In this paper, we explore the scientific- and industry-related literature to present a comprehensible survey on visualization methods for smart grids control and monitoring.